This research paper investigates the efficiency of hybrid vibration control systems combining tuned mass dampers (TMDs) and magnetorheological (MR) dampers for the reduction of seismic vibrations in asymmetric ten-story reinforced concrete buildings. An extensive three-dimensional mathematical representation with two-way eccentricities is formulated that takes into consideration realistic torsional coupling effects. Six historic earthquake records with varied seismic features are used as ground motions scaled to a standard peak ground acceleration of 0.35 g. Five different control settings are test 1. uncontrolled baseline, 2. TMD-only system with 3% mass ratio, 3. MR-only system with four dampers in Passive-On mode, 4. hybrid TMD-MR system with passive control, and 5. hybrid TMD-MR system with a new Response-Tracking Semi-Active Control (RT-SAC) algorithm. Findings indicate that the hybrid RT-SAC setup is superior in performance with an average peak roof displacement reduction of 59.2%, maximum inter-story drift reduction of 46.8%, peak floor acceleration reduction of 48.5%, and base shear reduction of 47.8% compared to the uncontrolled setup. One-way ANOVA statistical analysis demonstrates that control strategy has a significant influence on structural responses (p & iexcl; 0.001), with control configuration accounting for 39.8% variance in peak displacement. The hybrid design offers a more consistent distribution of inter-story drift, with the maximum drift reduced to 1.18% (below the 2.23% exceeding code limits). Energy dissipation analysis indicates that the hybrid system dissipates 48.8% more energy than the uncontrolled structure while requiring a sensible amount of control energy of 92.5 kJ.
This study investigates axial buckling of sandwich composite shells with anti-tetrachiral lattice cores and graphene-reinforced surfaces, analytically deriving mechanical properties for GPL distributions: uniform (UD), V-pattern (FG-V), and X-pattern (FG-X). The fundamental formulas are formed utilizing Reddy higher-order shear deformation theory (HSDT) and minimize the total potential energy principle. The Navier solution tactic is employed to extract the characteristic equation of the system, which is subsequently resolved to calculate the critical buckling load for different geometric and mechanical parameter configurations. The results reveal that volume fraction and distribution of GPLs significantly influence the buckling load, with optimal performance being contingent upon the geometric constraints of the lattice core. By optimizing the lattice core specifications, the highest buckling load can be achieved with minimal GPL volume fraction, enhancing the economic feasibility of nanoparticle usage in such structures. Notably, the FG-V distribution with a 0.05 wt.% GPL demonstrates the most efficient configuration for maximizing the buckling load. The results emphasize the importance of optimizing the geometry of the lattice core to achieve the maximum buckling load. Specifically, for a lattice configuration with Rx/Ry = 1.5, the optimal inclination angle of 10 degrees leads to a 0.8% increase in buckling load compared to other angles. Similarly, for Rx/Ry = 1, the highest buckling load is obtained at an inclination angle of 60 degrees, which is approximately 30% greater than the minimum buckling load observed. These findings highlight the critical role of geometric optimization in maximizing the structural stability and performance of bi-curved sandwich composite shells.
Utility-scale solar farms require reliable design of tens of thousands of driven steel pile foundations, where wind-induced uplift governs. Spatial variability of the shallow subsurface and limited cone penetration test (CPT) coverage mean pile reliability depends on distance from the nearest test - an uncertainty Eurocode 7 does not capture. This paper proposes a probabilistic methodology combining sequential Gaussian simulation (SGS) of CPT data with three capacity methods (LCPC, AFNOR NF P 94-262 and ICP-05) and FOSM/FORM reliability analysis to quantify uplift reliability along linear Chains connecting adjacent CPT locations. The methodology is applied to a solar farm in Pleistocene sandy deposits with 70 CPTs. Two Chains are analyzed: a 309 m Chain through five CPTs in a uniform zone and a 302 m Chain through four CPTs in a variable zone. Pile reliability is governed by two independent contributions. The first is conditioning geometry: the COV of uplift resistance is smallest at CPT locations and grows with distance, forming a wave-like profile with minima of 1.4-2.7% at CPTs and maxima of 3.2-6.1% at midpoints. The second is geological variability: differences in soil strength shift the mean resistance and dominate the reliability index wherever the deposit is non-uniform. Along Chain 1, the FORM reliability index /3 varies only moderately, driven almost entirely by conditioning geometry. Along Chain 2, /3 spans a range over three times wider, reflecting dominant geological heterogeneity. The Chain-based framework provides a site-specific basis for separating these contributions, for optimizing CPT spacing and delineating geological zones.
The behaviour of columns in irregular structures subjected to seismic effects is significantly influenced by torsional moments arising primarily due to asymmetries in the plan. Torsional moments that occur during earthquakes in irregular buildings have a negative impact on the load-bearing capacity and ductility of columns. Therefore, it is crucial to understand how columns behave when subjected to axial loads and torsional effects in order to ensure safe structural design. Seven column specimens were tested under various axial load ratios. The columns represent residential buildings constructed in earthquake zones prior to 2000 in Turkiye, which do not even meet the seismic code requirements of their construction periods in terms of material properties, longitudinal and transverse reinforcement ratios, and restraint details. This experimental study examined torsional moment capacity, cracking and ultimate rotation values, stiffness loss, ductility and energy dissipation parameters. These were then compared with finite element analyses performed using ABAQUS software. The results reveal that axial load-torsion interaction plays a decisive role in the seismic behaviour of columns, exhibiting a nonlinear character. The findings suggest that there is an optimum axial load range, and that exceeding this range significantly reduces torsional ductility. The study suggests that adequate transverse reinforcement, appropriate detailing and an optimum axial load ratio are crucial for the torsional behaviour of reinforced concrete columns.
Problematic expansive soils from the Guabirotuba Formation present engineering challenges, some of them are low shear strength and high compressibility. This research addresses these problems by evaluating the mechanical behavior of this soil when stabilized with lime-activated silica fume (SF) and reinforced with polypropylene fibers (PPF). The experimental program evaluated mixtures containing 6-12% SF, 9% lime, and 0.5% PPF through unconfined compressive strength (UCS), splitting tensile strength (STS), and consolidated undrained (CU) triaxial tests, alongside scanning electron microscopy(SEM). The main findings reveal that lime is essential to activate the pozzolanic reaction of SF. The lime-SF blends form a Calcium Silicate Hydrate (C-S-H) matrix, significantly increasing UCS and STS. While the inclusion of PPF slightly reduced peak STS and had a negligible effect on peak UCS, its primary contribution was transforming the failure mode from brittle to ductile by bridging micro-cracks and preventing abrupt failure. Furthermore, triaxial testing demonstrated that fiber reinforcement consistently increases effective cohesion (c') but decreases the effective friction angle (phi'). SEM analysis corroborated these macroscopic findings, illustrating a densified matrix and strong fiber-matrix adhesion. This study demonstrates that the synergistic use of lime, SF, and PPF enhances the mechanical stability and ductility of Guabirotuba soil, which is relevant in geotechnical engineering applications such as pavement layers, embankments, and earth structures where enhanced post-peak behavior and structural integrityare desirable.
Sustainable concrete can be created by replacing cement with ceramic and brick waste in appropriate proportions. Using brick tile powder (BTP) and ceramic tile powder (CTP) as SCMs is cost-efficient because they recycle ceramic industry waste and offer new output disposal methods. In this study, the effect of replacing cement with BTP and CTP in different ratios and finenesses on workability and strength properties of the mixture was investigated. A sustainability analysis was conducted to estimate the environmental impact of using BTP or CTP as a partial substitute for cement. The performance index approach was used to select the suitable replacement level to obtain a multifunctional mortar mix. Findings reveal that partial replacement of cement with BTP or CTP results in more environmentally friendly binders, reducing production costs and carbon emissions without compromising compressive strength. 20% cement replacement demonstrates a balance between cost efficiency, carbon emission reduction, and compressive strength.
Urban regions are under increasing pressure due to the economic, social, and environmental domains with a steady upward trend in the motor vehicle numbers. Consequently, the demand for liquid fuel oil rises, necessitating gasoline station construction both inside and outside cities. Gasoline stations remain more dangerous even with the adoption of contemporary methods for storing petroleum products and stringent construction and operation guidelines. Furthermore, they pose a risk of hazardous fire and explosion to both humans and buildings. A Geographic Information System (GIS) tool has been developed to model the impacts of gasoline station explosions in urban areas. The tool visualizes relevant variables, such as size of the fireball, danger zone of possible self-emitting combustion, impacted zone of the spilled gasoline combustion, zones of human injuries ranging from 1st degree burns to painful sensations on the skin and mucous membranes, and zones of building damage ranging from total destruction to minor damage. Apart from the danger buffer visualization, affected buildings are extracted, and queries are presented to extract the key statistics. The current study applies the developed strategy to gasoline station network in Tashkent, Uzbekistan, as a case study, to assure model applicability. The study produced encouraging results when assessing station explosion scenarios and displaying danger, human injury, and building damage zones. The model has the advantage of assessing a large collection of gasoline stations automatically, saving time and effort for emergency management while analysing large datasets with hundreds of stations and thousands of buildings in real operation.
Magnesium phosphate cement (MPC) can be used as a rapid repair material due to its excellent mechanical properties and high bonding strength. However, the properties of MPC are significantly influenced by the environment but have been poorly studied in previous research. This paper researched the effects of four curing conditions on the properties and microstructures of hardened MPC, and the bonding mechanism between the MPC and OPC mortar was also investigated. The experimental results showed that water conditions decreased the mechanical strength and bonding strength compared to standard conditions, increasing the volume of large pores due to the dissolution of hydration products. Meanwhile, the phosphate hydrates were highly soluble in the alkaline solutions, leading to a significant increase in total porosity, but the compressive strength and bonding strength were not decreased due to the physical filling effect and chemical reaction of Ca(OH)2. Additionally, the high temperature inhibited the hydration process of MPC, enhancing the decomposition of the main hydration product, and the bonding strength sharply decreased. Finally, the bonding mechanism between MPC and OPC included mechanical interlocking and chemical reactions. The former lost its effect in the heat due to the cracks and broken interfaces, and the latter was diminished in the wet environment for the phosphate was more likely to dissolve in the water instead of penetrating into the OPC phase. Therefore, the MPC is not suitable for wet environments and high-geothermal environments.
Lime mortar is one of the oldest building materials used since ancient times in temples and historical monuments that still stand today. It is characterized by its role as a natural binder, its relative flexibility, and its compatibility with traditional stone materials, which makes it suitable for restoration and maintenance of historical structures. However, lime mortar faces fundamental challenges that limit its use in advanced construction applications. With the evolving need to preserve historical heritage and develop more sustainable and environmentally friendly building materials, research has focused on integrating nanomaterials with traditional mortar to enhance its mechanical and physical properties. Carbon nanotubes (CNTs) have shown positive effects when incorporated with various materials due to their unique mechanical and physical properties. The combination of lime mortar as a traditional and environmentally friendly material with CNTs as a modern reinforcing material enables the development of a composite that merges traditional authenticity with high mechanical performance. This research aims to investigate the effect of incorporating CNTs in varying proportions within lime mortar and to evaluate their impact on compressive and flexural strength, as well as internal structure and porosity. CNTs have been synthesized and purified, then SEM-EDX and TEM analyses were conducted prior to mixing with lime mortar in ratios of 0.01%, 0.03% and 0.3%, followed by mechanical and physical testing of the prepared samples, but the results did not achieve the desired outcomes.
The Hoek-Brown failure criterion is a cornerstone of rock mechanics and is widely applied in the design of underground excavations, slopes, and foundations. However, determining its intact rock constant (mi) conventionally requires multiple triaxial compression tests under varying confining pressures, which are costly, time-consuming, and often infeasible when core quality or sample availability is limited. Building upon recent advances in empirical, probabilistic, and elastic-based approaches, this study develops and validates a practical method for estimating mi from standard uniaxial compressive strength (UCS) tests through analysis of the stress-dependent Poisson's ratio. The proposed framework establishes a mechanical linkage between mi and the lateral deformation behavior of intact rock, reflecting the influence of microcrack closure and brittleness. Extensive UCS data for granite, limestone, marl, sandstone, and rock salt were analyzed to evaluate the method's reliability. The estimated mi values show excellent agreement with triaxial test results for brittle lithologies and acceptable accuracy for more ductile rocks. Monte Carlo uncertainty analysis confirms the robustness of the approach, particularly for crystalline and well-cemented formations. The method offers a cost-effective and theoretically grounded alternative for preliminary design and rock characterization where triaxial testing is impractical, thereby enhancing the applicability of the Hoek-Brown criterion in routine engineering practice.
Geotechnical design is greatly influenced by spatial variability of soil properties, uncertainty of modelling, and lack site investigation information. Traditional deterministic procedures do not directly define failure probability or the economic value of additional data, while strong design optimization may produce overly conservative solutions with no explicit cost-benefit evaluation. This study proposes an integrated probabilistic program that consolidates Spatial Random Fields (SRFs), Bayesian Networks (BNs), and Value of Information (VOI) analysis to support risk-informed geotechnical site characterization. To minimize the computational burden linked with high-dimensional random fields, the spatial variability is converted into minimized variables suitable for Bayesian inference and pre-posterior decision analysis. The proposed framework allows efficient determinations of the Expected Value of Sample Information (EVSI) and Expected Net Benefit of Sampling (ENBS) for alternative investigation protocols. Two representative case studies are studied: slope stability as an ultimate limit-state problem and shallow foundation settlement as a serviceability limit-state problem. The results reveal that the optimal sampling location is mechanism-dependent, shifting from the slope toe for stability assessment to the foundation center for settlement control. Validation against independent Monte Carlo simulations shows strong agreement, with (R2 approximate to 0.95) for the reduced order prediction. The proposed framework also produces up to (143%) improvement in economic efficiency compared with conventional investigation procedures. The framework therefore presents a practical-basis for economically optimized, risk-informed site investigation planning and future geotechnical digital twin applications.
High-profiled sheets (HPS) are widely used in the construction of numerous building structures. The constant development of new forms of sheet profiling in order to optimize these elements compelled the designers to determine their strength, which is a complex process, especially if traditional analytical methods are used. On the other hand, the Finite Element Method (FEM) represents a good alternative to analytical calculations and experimental testing that require significant financial investments. However, the available information on the modeling of these structural elements is insufficient. This paper presents the development of a numerical model of HPS made of structural steel. The pronounced profile height causes a stability problem, so a geometrically and materially non-linear analysis with imperfections (GMNIA) was carried out. The developed numerical model should serve as a basis for further research into improving the manufacturer's data on strength of the HPS. The paper specifically addresses the influence of geometric imperfections on the strength. The shape and size of the imperfections were analyzed and their critical size leading to failure was determined. To confirm the reliability of the developed numerical model, load-bearing analyses were performed with varying the length of the contact area and the number of fasteners for connecting the HPS to the supporting structure. The developed numerical model showed very good agreement with the experimental analysis, carried out by author, both for the ultimate limit state and the serviceability limit state, so the numerical model was successfully validated.
Composite girders with corrugated webs and embedded shear connections have been developed in bridge design practice, making structures more advantageous compared to conventional composite structures with flat web and headed studs. To understand the structural behavior and determine the influence of structural parameters on longitudinal shear resistance, experimental and numerical testing of embedded shear connectors is essential. An experimental program of 43 push-out tests on embedded specimens with trapezoidal steel profiles has been completed at the Budapest University of Technology and Economics. Current paper presents a detailed evaluation of the experimental results of the full-scale push-out test series, focusing on structural parameters causing concrete failure (trapezoidal profile geometry, embedding depth, shear connectors). To investigate the influence of structural parameters (number and geometry of cutouts) on the failure modes of the corrugated steel web, a numerical model is developed. The study aims to investigate how structural parameters of the embedded corrugated web influence its behavior and failure modes, with particular focus on avoiding non-visible steel deterioration through appropriate detailing. The objective is to identify structural parameters that lead to concrete deterioration, occurring only after significant crack propagation, so that failure becomes visible before it happens. Conclusions are drawn based on the results of experimental and numerical investigations.
To address the challenge of detecting damage in a large number of in-service small and medium-span bridges, this study proposes a damage identification method based on a multi-branch convolutional neural network (CNN) under moving loads. Two CNN architectures-a dual-branch model and a multi-branch model-are developed for structural damage identification. The sensitivity of damage identification to sensor location is also investigated. First, various damage scenarios are simulated using a finite element model of a bridge. The structure is excited by a moving vehicle load, and the resulting structural vibration responses are extracted through transient analysis. These responses are then used as input to train and validate the established CNN models. Finally, the effectiveness and accuracy of the proposed method are verified through a laboratory-scale model test. The results demonstrate that both the dual-branch and multi-branch CNN models exhibit higher computational efficiency and better identification performance than a single-branch CNN model under multiple damage scenarios. Furthermore, the identification results show no obvious difference among sensors placed at different locations for the same damage case.
Aggregates play a crucial role in geotechnical engineering, serving applications such as railway and road construction, hydraulic structures, and as the base material for concrete. While various tests are commonly employed to characterize aggregates, the Aggregate Impact Value (AIV) can also provide indirect information on fundamental rock properties. In this study, AIV was used to estimate Uniaxial Compressive Strength (UCS) and Brazilian Tensile Strength (BTS) for very weak, fractured, and altered rocks where preparing standard specimens is challenging or impossible. Statistical analyses were performed separately for two categories to support preliminary engineering assessments: weak rocks (dacite, limestone, lapilli tuff and claystone) (UCS < 50 MPa) and altered dacitic rocks. The results revealed a strong and statistically significant inverse correlation between AIV and both UCS and BTS across all categories. The coefficients of determination (R2) for the best-fitting regression models ranged from 0.87 to 0.94, indicating high predictive performance. Predicted UCS and BTS values based on AIV exhibited strong agreement with measured values, with correlation coefficients (r) between 0.90 and 0.96. These findings confirm the reliability of AIV as a predictive tool for mechanical properties in challenging rock environments. Overall, the proposed AIV-based regression equations provide a practical and efficient approach for preliminary assessment of UCS and BTS, offering valuable insight for geotechnical design when conventional sample preparation is difficult or infeasible.
This paper investigates the dynamic behaviour of a rolling ball absorber moving along a circular track whose surface is formed by a pair of rails. The rail geometry constrains the motion of the ball to a planar trajectory. Experimental measurements of free oscillations are recorded using a video camera and subsequently processed by a presented algorithm. The output of the algorithm is the angular displacement of the absorber ball as a function of time. The free-vibration response is further analysed by fitting a numerical simulation to the experimentally obtained time history. The equations of motion are derived for a physical model consistent with the experimental setup and include a combination of viscous damping and rolling resistance to describe energy dissipation. The fitting procedure aims to identify an optimal combination of viscous and rolling damping coefficients that yields the best agreement between the numerical simulation and the experimental response.
To extend the applicability of optimization methods in civil engineering, particularly for structural members incorporating cementbased materials like concrete, this study proposes a stress-based bi-directional evolutionary structural optimization (BESO) framework integrated with incremental nonlinear structural analysis. The core objective is to minimize peak stress in structures by leveraging the p-norm function (p = 4-6) to approximate stress concentration and sensitivity numbers derived via the adjoint method. The proposed approach is validated for optimizing structures with highly nonlinear material behaviors. By tuning the p-value (4-6) during optimization, solutions aligned with predetermined objectives are achieved through element sensitivity analysis. The sensitivity numbers are computed by filtering initial values derived from incremental nonlinear stress analysis results. Subsequent sensitivity filtering and iterative design variable updates ensure convergence to stable solutions matching the optimization goals. The method incorporates von Mises stress for nonlinear material modeling and addresses numerical challenges like mesh dependency through dual filtering strategies as verified by two-dimensional/three-dimensional examples including irregular beams and cantilever structures. This framework provides a robust tool for topology optimization of civil structures with strongly nonlinear materials, balancing accuracy and computational efficiency under volume constraints.
This study develops a high-fidelity multi-objective static and dynamic scheduling model for dual-tunnel construction. To overcome topological deadlocks in tightly restricted spaces, complemented by a fine-grained time-slice mapping mechanism to eliminate resource fragmentation. At the static level, the optimization aims to minimize both the total make-span and the Weighted Resource Fluctuation Standard Deviation. A Memetic Algorithm-based Hybrid Genetic Algorithm (HGA) is proposed to solve the NP-hard problem. The algorithmic engine is fundamentally upgraded by incorporating an unbiased topological sequence initialization to expand the early exploration space, a dynamic continuity penaltyfunction to ensure intra-cycle operational fluidity, and an elite local search strategyto overcome genetic hardening. Furthermore, the epsilon-constraint method is utilized to extract the exact Pareto front. An application to a 100-meter dual-tunnel engineering case demonstrates that the proposed HGA possess significant global optimization capabilities, while the rolling-horizon dynamic scheduling exhibits superior computational efficiency. The static optimization reduced the construction duration by 13.3%compared to the actual schedule, while the dynamic optimization achieved a 11.5% reduction under ideal conditions. Furthermore, disturbance simulation experiments confirm that this dynamic scheduling mechanism maintains a linear and stable increase in predicted duration across various disturbance scenarios, demonstrating excellent stability and robustness.
An elastoplastic constitutive model is proposed to account for stress loading effects based on triaxial test results of granite rockfill materials. The model utilizes an extended yield function to flexibly control the yield surface shape, distinguishing between loading, unloading, and neutral loading conditions. A non-associated flow rule is implemented, incorporating a critical dilatancy stress ratio into the dilatancy equation to capture particle breakage behavior. The model primarily focuses on the formulation of a stress-pathindependent hardening parameter based on the dilatancy equation. A total of 12 model parameters are introduced, all of which can be determined from two conventional laboratory geotechnical tests. Finally, the validity of the proposed model is verified through triaxial test results of various rockfill materials.
This study investigates the free vibration behavior of porous functionally graded beams using Timoshenko theory on a Winkler- Pasternak foundation. Such beams are commonly used in practical engineering applications, including aerospace structures and civil engineering components, where vibration control and weight efficiency are critical. The main advantage of the proposed method lies in its ability to capture the coupled effects of porosity and material gradation on transverse shear behavior, which are neglected in classical models using constant shear factors. The effects of key parameters are analyzed, including the material gradation index material, the foundation coefficients, porosity distributions, and transverse shear deformation through an adjusted correction factor. The governing equations of motion are derived using Hamilton's principle. The formulation is generally applicable to different boundary conditions, material configurations, and elastic foundation parameters. The proposed model is validated through comparisons with results from the literature, demonstrating agreement and confirming its reliability. The numerical results indicate that increasing the gradation index materials leads to a reduction in natural frequencies due to decreased material stiffness, an effect that becomes more pronounced for higher vibration modes. Conversely, the combined influence of the foundation parameters results in an increase in natural frequencies, highlighting the stiffening effect of the foundation. The shear correction factor decreases with increasing index material. Finally, comparing the natural frequencies obtained using a shear correction factor for isotropic materials with those of corrected porous FGM materials highlights the need to include coupled porosity-gradation effects in the dynamic analysis of FGM beams.
